Dataset Information

Integrated analysis of the gene expression profile and DNA methylation profile of obese patients with type 2 diabetes.

ABSTRACT: In order to better understand the etiology of obese type 2 diabetes (T2D) at the molecular level, the present study investigated the gene expression and DNA methylation profiles associated with T2D via systemic analysis. Gene expression (GSE64998) and DNA methylation profiles (GSE65057) from liver tissues of healthy controls and obese patients with T2D were downloaded from the Gene Expression Omnibus database. Differentially?expressed genes (DEGs) and differentially?methylated genes (DMGs) were identified using the Limma package, and their overlapping genes were additionally determined. Enrichment analysis was performed using the BioCloud platform on the DEGs and the overlapping genes. Using Cytoscape software, protein?protein interaction (PPI), transcription factor target networks and microRNA (miRNA) target networks were then constructed in order to determine associated hub genes. In addition, a further GSE15653 dataset was utilized in order to validate the DEGs identified in the GSE64998 dataset analyses. A total of 251 DEGs, including 124 upregulated and 127 downregulated genes, were detected, and a total of 9,698 genes were demonstrated to be differentially methylated in obese patients with T2D compared with non?obese healthy controls. A total of 103 overlapping genes between the two datasets were revealed, including 47 upregulated genes and 56 downregulated genes. The identified overlapping genes were revealed to be strongly associated with fatty acid and glucose metabolic pathways, in addition to oxidation/reduction. The overlapping genes cyclin D1 (CCND1), PPARG coactivator ? (PPARGC1A), fatty acid synthase (FASN), glucokinase (GCK), steraroyl?coA desaturase (SCD) and tyrosine aminotransferase (TAT) had higher degrees in the PPI, transcription target networks and miRNA target networks. In addition, among the 251 DEGs, a total of 35 DEGs were validated to be being shared genes between the datasets, which included a number of key genes in the PPI network, including CCND1, FASN and TAT. Abnormal gene expression and DNA methylation patterns that were implicated in fatty acid and glucose metabolic pathways and oxidation/reduction reactions were detected in obese patients with T2D. Furthermore, the CCND1, PPARGC1A, FANS, GCK, SCD and TAT genes may serve a role in the development of obesity?associated T2D.

SUBMITTER: Shen J

PROVIDER: S-EPMC5983955 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Integrated analysis of the gene expression profile and DNA methylation profile of obese patients with type 2 diabetes.

Shen Juan J Zhu Bin B

Molecular medicine reports 20180328 6

In order to better understand the etiology of obese type 2 diabetes (T2D) at the molecular level, the present study investigated the gene expression and DNA methylation profiles associated with T2D via systemic analysis. Gene expression (GSE64998) and DNA methylation profiles (GSE65057) from liver tissues of healthy controls and obese patients with T2D were downloaded from the Gene Expression Omnibus database. Differentially‑expressed genes (DEGs) and differentially‑methylated genes (DMGs) were ...[more]

PMID: 29620215

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Project description:BACKGROUND:Severe obesity is a growing, worldwide burden and conventional therapies including radical change of diet and/or increased physical activity have limited results. Bariatric surgery has been proposed as an alternative therapy showing promising results. It leads to substantial weight loss and improvement of comorbidities such as type 2 diabetes. Increased adiposity is associated with changes in epigenetic profile, including DNA methylation. We investigated the effect of bariatric surgery on clinical profile, DNA methylation, and biological age estimated using Horvath's epigenetic clock. RESULTS:To determine the impact of bariatric surgery and subsequent weight loss on clinical traits, a cohort of 40 severely obese individuals (BMI = 30-73 kg/m2) was examined at the time of surgery and at three follow-up visits, i.e., 3, 6, and 12 months after surgery. The majority of the individuals were women (65%) and the mean age at surgery was 45.1 ± 8.1 years. We observed a significant decrease over time in BMI, fasting glucose, HbA1c, HOMA-IR, insulin, total cholesterol, triglycerides, LDL and free fatty acids levels, and a significant small increase in HDL levels (all p values < 0.05). Epigenome-wide association analysis revealed 4857 differentially methylated CpG sites 12 months after surgery (at Bonferroni-corrected p value < 1.09 × 10-7). Including BMI change in the model decreased the number of significantly differentially methylated CpG sites by 51%. Gene set enrichment analysis identified overrepresentation of multiple processes including regulation of transcription, RNA metabolic, and biosynthetic processes in the cell. Bariatric surgery in severely obese patients resulted in a decrease in both biological age and epigenetic age acceleration (EAA) (mean = - 0.92, p value = 0.039). CONCLUSIONS:Our study shows that bariatric surgery leads to substantial BMI decrease and improvement of clinical outcomes observed 12?months after surgery. These changes explained part of the association between bariatric surgery and DNA methylation. We also observed a small, but significant improvement of biological age. These epigenetic changes may be modifiable by environmental lifestyle factors and could be used as potential biomarkers for obesity and in the future for obesity related comorbidities.

Project description:BACKGROUND:Ovarian cancer is an epithelial malignancy that intrigues people for its poor outcome and lack of efficient treatment, while methylation is an important mechanism that have been recognized in many malignancies. In this study, we attempt to assess abnormally methylated gene markers and pathways in ovarian cancer by integrating three microarray datasets. METHODS:Three datasets including expression (GSE26712 and GSE66957) and methylation (GSE81224) datasets were accessed. GEO2R platform was used to detect abnormally methylated-differentially expressed genes. Protein-protein interaction (PPI) networks were built and analysed for hypermethylated and hypermethylated differentially expressed genes using Cytoscape software and Mcode app. GEPIA and cBioPortal platforms were used to validate the expression of the hub genes and the correlation between their mRNA expressions and methylation levels. Kaplan Meier-plotter platform were used to assess the prognostic significance of the hub genes. RESULTS:Six hundred eighty-one hypomethylated-upregulated genes were detected and involved in Rap1 signaling pathway, biosynthesis of amino acids, endocrine resistance, apoptosis, pathways in cancer. The hub genes were TNF, UBC, SRC, ESR1, CDK1, PECAM1, CXCR4, MUC1, IKBKG. Additionally, 337 hypermethylated-downregulated genes were detected and involved in pathways in cancer, focal adhesion, sphingolipid signaling pathway, EGFR tyrosine kinase inhibitor resistance, cellular senescence. The hub genes were BDNF, CDC42, CD44, PPP2R5C, PTEN, UBB, BMP2, FOXO1, KLHL2. TNF, ESR1, MUC1, CD44, PPP2R5C, PTEN, UBB and FOXO1 showed significant negative correlation between their mRNA expressions and methylation levels. TNF, ESR1 and FOXO1 showed prognostic significance. CONCLUSIONS:Two novel gene networks were found for ovarian cancer. TNF, ESR1, MUC1 and FOXO1 are our candidate genes that might take part in ovarian cancer progression in an epigenetic approach, TNF, ESR1 and FOXO1 may serve as potential markers for ovarian cancer prognosis evaluation.

Dataset Information

Integrated analysis of the gene expression profile and DNA methylation profile of obese patients with type 2 diabetes.

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Integrated analysis of the gene expression profile and DNA methylation profile of obese patients with type 2 diabetes.

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